Voc AI Chatbot

Most support bots stop at a canned reply, which is why buyers type "agent" three times. This AI chatbot for e-commerce looks up the order, checks the shipping record and applies your after-sales policy before it answers. The vendor reports more than 70% of common inquiries resolved without a human and 80% or higher reply accuracy, both measured on its own customer projects. Those numbers only hold once your knowledge base is complete.

On a product page, the chat widget knows which SKU the buyer is looking at, so a question about a sofa's width gets the real measurement rather than a generic answer. It handles pre-sale questions first and passes conversations that need judgment to an agent with the history intact. For stores with a thin catalogue this is a small gain. For stores with 200 variants and confusing specs, it's the difference between a sale and an abandoned cart.

Phone support is where small teams bleed time. The voice agent answers calls in the customer's language, collects the reason for the call and hands the call to a person with a recording, a transcript and a summary already attached. Calls and messages land in the same inbox as chats, so nobody has to check two systems. Voice is billed by the minute on top of the seat price.

The AI escalates when it can't find a reliable source, when a case involves compensation beyond policy, when a buyer is clearly upset or asks for a person, and when compliance questions come up. An agent takes over with one click and can hand follow-up back to the AI afterwards. Refunds and address changes run as write actions that need approval, and payment card details stay outside the AI's reach.

The agent remembers earlier conversations and order history, so a repeat buyer doesn't restate their problem from scratch. That matters most in categories where the same person comes back for parts, accessories or a second purchase. Memory also shortens the average conversation, which is where the per-minute and per-credit costs come from.

Every conversation carries an owner, a status and internal notes, so the next teammate sees what happened and what should happen next. Calls, chats and SMS sit together with transcripts and recordings. Full context matters when a support request turns into a dispute later, and it's the part small teams usually lose when they run support out of a shared phone.

AI tagging and root-cause reports show which question types keep landing on a human, and where the knowledge base has holes. That's the useful half of support analytics: not a CSAT score, but a list of the questions worth writing a policy for. Without those reports, knowledge maintenance turns into guesswork.

The agent connects to order, logistics, inventory, ERP and ticketing systems, and it answers from live data instead of a static FAQ. A standard rollout covers assessment, training, testing and the first use cases inside about four weeks. More channels and more systems add time.